Evidence-Based Therapist-Supported Digital Mental Health Intervention for Patients Experiencing Medical Multimorbidity: A Retrospective Cohort Intent-to-Treat Study.

OBJECTIVE: Multimorbidity or the co-occurrence of multiple health conditions is increasing globally and is associated with significant psychological complications. It is unclear whether digital mental health (DMH) interventions for patients experiencing multimorbidity are effective, particularly given that this patient population faces more treatment resistance. The goal of the current study was to examine the impact of smartphone-delivered DMH interventions for patients presenting with elevated internalizing symptoms that have reported multiple lifetime medical conditions. METHODS: This preregistered (see https://osf.io/vh2et/ ) retrospective cohort intent-to-treat study with 2819 patients enrolled in a therapist-supported DMH intervention examined the associations between medical multimorbidity (MMB) and mental health outcomes. RESULTS: Results indicated that more MMB was significantly associated with greater presenting mental health symptom severity. MMB did not have a deleterious influence on depressive symptom trajectories across treatment, although having one medical condition was associated with a steeper decrease in anxiety symptoms compared to patients with no medical conditions. Finally, MMB was not associated with time to dropout, but was associated with higher dropout and was differentially associated with fewer beneficial treatment outcomes, although this is likely attributable to higher presenting symptom severity, rather than lesser symptom reductions during treatment. CONCLUSIONS: Overall, the Meru Health Program was associated with large effect size decreases in depressive and anxiety symptoms regardless of the number of MMB. Future DMH treatments and research might investigate tailored barrier reduction and extended treatment lengths for patients experiencing MMB to allow for greater treatment dose to reduce symptoms below clinical outcome thresholds.

Digital mental health interventions as stand-alone vs. augmented treatment as usual.

BACKGROUND: Smartphone-based digital mental health interventions (DMHI) have been described as a purported solution to meet growing healthcare demands and lack of providers, but studies often don't account for whether patients are concurrently in another treatment modality. METHODS: This preregistered quasi-experimental intent-to-treat study with 354 patients enrolled in a therapist-supported DMHI examined the treatment effectiveness of the Meru Health Program (MHP) as a stand-alone treatment as compared to the MHP in combination with any other form of treatment, including (1) in-person therapy, (2) psychotropic medication use, and (3) in-person therapy and psychotropic medication use. RESULTS: Patients with higher baseline depressive and anxiety symptoms were more likely to self-select into multiple forms of treatment, an effect driven by patients in the MHP as adjunctive treatment to in-person therapy and psychotropic medication. Patients in combined treatments had significantly higher depressive and anxiety symptoms across treatment, but all treatment groups had similar decreasing depressive and anxiety symptom trajectories. Exploratory analyses revealed differential treatment outcomes across treatment combinations. Patients in the MHP in combination with another treatment had higher rates of major depressive episodes, psychiatric hospitalization, and attempted death by suicide at baseline. CONCLUSIONS: Patients with higher depressive and anxiety symptoms tend to self-select into using DMHI in addition to more traditional types of treatment, rather than as a stand-alone intervention, and have more severe clinical characteristics. The use the MHP alone was associated with improvement at a similar rate to those with higher baseline symptoms who are in traditional treatments and use MHP adjunctively.

Daily links between objective smartphone use and sleep among adolescents.

INTRODUCTION: Concerns abound on how digital technology such as smartphone use may impair adolescent sleep. Although these linkages are supported in cross-sectional studies, research involving intensive longitudinal assessments and objective measures has called into question the robustness of associations. METHODS: In this study, a sample of ethnically diverse U.S. adolescents (N = 71; Mage = 16.49; 56% girls) wore Fitbit devices and submitted screenshots of their smartphone screen time, pickups, and notifications over a 14-day period in 2021. The Fitbits recorded nightly sleep quality and sleep onset. Adolescents also completed daily diaries reporting the previous night's sleep onset time and sleep quality. RESULTS: On days when adolescents engaged in greater nighttime screen time and, to some extent, pickups relative to their own average, they also had poorer sleep outcomes that night. Greater screen time was associated with later self-reported and Fitbit-recorded sleep onset and poorer self-reported sleep quality. Greater pickups was associated with later self-reported and Fitbit-recorded sleep onset. Smartphone use during the day did not relate to sleep outcomes, indicating the importance of distinguishing nighttime from daytime use. CONCLUSIONS: Parents and clinicians should help adolescents develop healthy digital skills to avoid exacerbating sleep problems that are known to occur during this developmental period.

Smartphone Photoplethysmography Pulse Rate Covaries With Stress and Anxiety During a Digital Acute Social Stressor.

OBJECTIVE: Heart rate is a transdiagnostic correlate of affective states and the stress diathesis model of health. Although most psychophysiological research has been conducted in laboratory environments, recent technological advances have provided the opportunity to index pulse rate dynamics in real-world environments with commercially available mobile health and wearable photoplethysmography (PPG) sensors that allow for improved ecologically validity of psychophysiological research. Unfortunately, adoption of wearable devices is unevenly distributed across important demographic characteristics, including socioeconomic status, education, and age, making it difficult to collect pulse rate dynamics in diverse populations. Therefore, there is a need to democratize mobile health PPG research by harnessing more widely adopted smartphone-based PPG to both promote inclusivity and examine whether smartphone-based PPG can predict concurrent affective states. METHODS: In the current preregistered study with open data and code, we examined the covariation of smartphone-based PPG and self-reported stress and anxiety during an online variant of the Trier Social Stress Test, as well as prospective relationships between PPG and future perceptions of stress and anxiety in a sample of 102 university students. RESULTS: Smartphone-based PPG significantly covaries with self-reported stress and anxiety during acute digital social stressors. PPG pulse rate was significantly associated with concurrent self-reported stress and anxiety ( b = 0.44, p = .018) as well as prospective stress and anxiety at the subsequent time points, although the strength of this association diminished the farther away pulse rate got from self-reported stress and anxiety (lag 1 model: b = 0.42, p = .024; lag 2 model: b = 0.38, p = .044). CONCLUSIONS: These findings indicate that PPG provides a proximal measure of the physiological correlates of stress and anxiety. Smartphone-based PPG can be used as an inclusive method for diverse populations to index pulse rate in remote digital study designs.

Longitudinal Patterns of Engagement and Clinical Outcomes: Results From a Therapist-Supported Digital Mental Health Intervention.

OBJECTIVE: Digital mental health interventions (DMHIs) are an effective treatment modality for common mental disorders like depression and anxiety; however, the role of intervention engagement as a longitudinal "dosing" factor is poorly understood in relation to clinical outcomes. METHODS: We studied 4978 participants in a 12-week therapist-supported DMHI (June 2020-December 2021), applying a longitudinal agglomerative hierarchical cluster analysis to the number of days per week of intervention engagement. The proportion of people demonstrating remission in depression and anxiety symptoms during the intervention was calculated for each cluster. Multivariable logistic regression models were fit to examine associations between the engagement clusters and symptom remission, adjusting for demographic and clinical characteristics. RESULTS: Based on clinical interpretability and stopping rules, four clusters were derived from the hierarchical cluster analysis (in descending order): a) sustained high engagers (45.0%), b) late disengagers (24.1%), c) early disengagers (22.5%), and d) immediate disengagers (8.4%). Bivariate and multivariate analyses supported a dose-response relationship between engagement and depression symptom remission, whereas the pattern was partially evident for anxiety symptom remission. In multivariable logistic regression models, older age groups, male participants, and Asians had increased odds of achieving depression and anxiety symptom remission, whereas higher odds of anxiety symptom remission were observed among gender-expansive individuals. CONCLUSIONS: Segmentation based on the frequency of engagement performs well in discerning timing of intervention disengagement and a dose-response relationship with clinical outcomes. The findings among the demographic subpopulations indicate that therapist-supported DMHIs may be effective in addressing mental health problems among patients who disproportionately experience stigma and structural barriers to care. Machine learning models can enable precision care by delineating how heterogeneous patterns of engagement over time relate to clinical outcomes. This empirical identification may help clinicians personalize and optimize interventions to prevent premature disengagement.

An RDoC-based approach to adolescent self-injurious thoughts and behaviors: The interactive role of social affiliation and cardiac arousal.

Recent theoretical models have posited that increases in self-injurious thoughts and behaviors (SITBs) during adolescence may be linked to failures in biological stress regulation in contexts of social stress. However, there is a lack of data examining this hypothesis during the transition to adolescence, a sensitive period of development characterized by changes across socioaffective and psychophysiological domains. Building on principles from developmental psychopathology and the RDoC framework, the present study used a longitudinal design in a sample of 147 adolescents to test whether interactions among experiences of social (i.e., parent and peer) conflict and cardiac arousal (i.e., resting heart rate) predicted adolescents' engagement in SITBs (i.e., nonsuicidal self-injury, NSSI; and suicidal ideation; SI) across 1-year follow-up. Prospective analyses revealed that adolescents experiencing a combination of greater peer, but not family, conflict and higher cardiac arousal at baseline showed significant longitudinal increases in NSSI. In contrast, social conflict did not interact with cardiac arousal to predict future SI. Findings indicate that greater peer-related interpersonal stress in adolescents may increase risk for future NSSI among youth with physiological vulnerabilities (i.e., higher resting heart rate) that may be markers of maladaptive stress responses. Future research should examine these processes at finer timescales to elucidate whether these factors are proximal predictors of within-day SITBs.

Trajectories of depression symptoms in a therapist-supported digital mental health intervention: a repeated measures latent profile analysis.

PURPOSE: Major depression affects 10% of the US adult population annually, contributing to significant burden and impairment. Research indicates treatment response is a non-linear process characterized by combinations of gradual changes and abrupt shifts in depression symptoms, although less is known about differential trajectories of depression symptoms in therapist-supported digital mental health interventions (DMHI). METHODS: Repeated measures latent profile analysis was used to empirically identify differential trajectories based upon biweekly depression scores on the Patient Health Questionnaire-9 (PHQ-9) among patients engaging in a therapist-supported DMHI from January 2020 to July 2021. Multivariate associations between symptom trajectories with sociodemographics and clinical characteristics were examined with multinomial logistic regression. Minimal clinically important differences (MCID) were defined as a five-point change on the PHQ-9 from baseline to week 12. RESULTS: The final sample included 2192 patients aged 18 to 82 (mean = 39.1). Four distinct trajectories emerged that differed by symptom severity and trajectory of depression symptoms over 12 weeks. All trajectories demonstrated reductions in symptoms. Despite meeting MCID criteria, evidence of treatment resistance was found among the trajectory with the highest symptom severity. Chronicity of major depressive episodes and lifetime trauma exposures were ubiquitous across the trajectories in a multinomial logistic regression model. CONCLUSIONS: These data indicate that changes in depression symptoms during DMHI are heterogenous and non-linear, suggesting a need for precision care strategies to address treatment resistance and increase engagement. Future efforts should examine the effectiveness of trauma-informed treatment modules for DMHIs as well as protocols for continuation treatment and relapse prevention.

Links Between Objectively-Measured Hourly Smartphone Use and Adolescent Wake Events Across Two Weeks.

PURPOSE: Psychosocial and bioregulatory pressures threaten sleep during adolescence. Although recent work suggests that the ubiquity of smartphone use throughout adolescence may also relate to poorer sleep outcomes, most existing research relies upon self-report and retrospective measures. This study drew upon objective measures of smartphone use and sleep at the hourly level to understand how smartphone use was associated with the duration of wake events during sleeping hours. METHODS: Across a 14-day daily study, 59 racially and ethnically diverse adolescents ages 15 to 18 had their sleep assessed via Fitbit Inspire 2 devices and uploaded screenshots of their screen time, pickups, and notifications as logged by their iPhone's iOS. Multi-level modeling was performed to assess hourly level associations between adolescent smartphone use and wake-events during their sleep sessions (N = 4,287 hourly cases). RESULTS: In hours during adolescents' sleep session with more screen time or pickups, adolescents had longer wake event duration. More notifications in a given hour were not associated with wake event duration in the same hour. CONCLUSIONS: Using objectively measured smartphone and sleep data collected at the hourly level, we found that during sleeping hours, when adolescents are actively engaging with their smartphones, their sleep is disrupted, such that their wake events are longer in that hour.

Concurrent and prospective associations between fitbit wearable-derived RDoC arousal and regulatory constructs and adolescent internalizing symptoms.

BACKGROUND: Adolescence is characterized by alterations in biobehavioral functioning, during which individuals are at heightened risk for onset of psychopathology, particularly internalizing disorders. Researchers have proposed using digital technologies to index daily biobehavioral functioning, yet there is a dearth of research examining how wearable metrics are associated with mental health. METHODS: We preregistered analyses using the Adolescent Brain Cognitive Development Study dataset using wearable data collection in 5,686 adolescents (123,862 person-days or 2,972,688 person-hours) to determine whether wearable indices of resting heart rate (RHR), step count, and sleep duration and variability in these measures were cross-sectionally associated with internalizing symptomatology. All models were also run controlling for age, sex, body mass index, socioeconomic status, and race. We then performed prospective analyses on a subset of this sample (n = 143) across 25 months that had Fitbit data available at baseline and follow-up in order to explore directionality of effects. RESULTS: Cross-sectional analyses revealed a small, yet significant, effect size (R2 = .053) that higher RHR, lower step count and step count variability, and greater variability in sleep duration were associated with greater internalizing symptoms. Cross-lagged panel model analysis revealed that there were no prospective associations between wearable variables and internalizing symptoms (partial R2 = .026), but greater internalizing symptoms and higher RHR predicted lower step count 25 months later (partial R2 = .010), while higher RHR also predicted lower step count variability 25 months later (partial R2 = .008). CONCLUSIONS: Findings indicate that wearable indices concurrently associate with internalizing symptoms during early adolescence, while a larger sample size is likely required to accurately assess prospective or directional effects between wearable indices and mental health. Future research should capitalize on the temporal resolution provided by wearable devices to determine the intensive longitudinal relations between biobehavioral risk factors and acute changes in mental health.

Adolescents Are More Likely to Help Others on Days They Take Risks and Crave Social Connections.

This study examined how adolescents' risk-taking behaviors were related to their prosocial behaviors on a daily level and how this association differed depending on adolescents' daily and average levels of sensation seeking and social craving. Adolescents (N = 212; Mage = 15 years) completed daily diaries for 14 days. Adolescents were more likely to engage in prosocial behavior on days when they also took risks, but only when they also felt high levels of social craving. The daily link between risk-taking and prosocial behavior did not vary based on daily or individual differences in sensation seeking. Results suggest that when adolescents feel highly motivated to connect with others, their risk-taking and prosocial tendencies co-occur on a daily basis.

Induction of acute stress through an internet-delivered Trier Social Stress Test as assessed by photoplethysmography on a smartphone.

Recent studies have demonstrated the feasibility of administering the Trier Social Stress Test (TSST) through the internet, with major implications for promoting inclusivity in research participation. However, online TSST studies to date are limited by a lack of control groups and the need for biological measures of stress reactivity that can be fully implemented online. Here, we test smartphone-based photoplethysmography as a measure of heart rate reactivity to an online variant of the TSST. Results demonstrate significant acceleration in heart rate and heightened self-reported stress and anxiety in the TSST condition relative to a placebo version of the TSST. The placebo condition led to a significant increase in self-reported stress and anxiety relative to baseline levels, but this increase was smaller in magnitude than that observed in the TSST condition. These findings highlight the potential for smartphone-based photoplethysmography in internet-delivered studies of cardiac reactivity and demonstrate that it is critical to utilize random assignment to a control or stressor condition when administering acute stress online.

Psychobiological markers of allostatic load in depressed and nondepressed mothers and their adolescent offspring.

BACKGROUND: A substantial body of research has emerged suggesting that depression is strongly linked to poor physical health outcomes, which may be partly due to increased allostatic load across stress response systems. Interestingly, health risks associated with depression are also borne by the offspring of depressed persons. Our aim was to simultaneously investigate whether maternal depression is associated not only with increased allostatic load across cardiac control, inflammation, cellular aging, but also if this is transmitted to adolescent children, possibly increasing the risk for early onset of psychiatric conditions and disease in these offspring. METHODS: A preregistered, case-control study of 180 low-income mothers (50% mothers depressed, 50% mothers nondepressed) and their adolescent offspring was conducted to determine how depressed mothers and their adolescent offspring systematically differ in terms of autonomic, sympathetic, and parasympathetic cardiac control; inflammation; cellular aging; and behavioral health in offspring, which are indicators suggestive of higher allostatic load. RESULTS: Findings indicate that depressed mothers and their adolescent offspring differ in terms of comorbid mental and physical health risk profiles that are suggestive of higher allostatic load. Findings indicate that depressed mothers exhibit elevated resting heart rate and decreased heart rate variability, and adolescent offspring of depressed mothers exhibit greater mental health symptoms, elevated heart rate, and accelerated biological aging (shorter telomeres). These effects persisted after controlling for a range of potential covariates, including medication use, sex, age, and adolescents' own mental health symptoms. CONCLUSIONS: Findings indicate that maternal depression is associated with increased allostatic load in depressed women and their adolescent children, possibly increasing risk for early onset of psychiatric conditions and disease in these offspring. Future research is needed to delineate why some biological systems are more impacted than others and to explore how findings might inform preventative programs targeted at adolescent offspring of depressed mothers.

Prior night sleep moderates the daily spillover between conflict with peers and family and diurnal cortisol.

We investigated whether daily experiences of conflict with family and peers were associated with fluctuations in diurnal cortisol, and whether sleep buffers the associations between conflict and diurnal cortisol. A racially diverse sample of 370 adolescents (ages 11-18; 57.3% female) provided daily diaries for 5 days and saliva samples for 4 days. Hierarchical linear models tested how peer and family conflict were associated with diurnal cortisol (i.e., total cortisol output, cortisol slope, and cortisol awakening response) the next day, and whether these associations were moderated by sleep duration the previous night. When adolescents experienced peer conflict, they showed higher area under the curve (AUC) the next day if they had slept less the night prior to conflict, but relatively lower cortisol awakening response (CAR) and flatter cortisol slope the next day if they had slept more the night prior to conflict. When adolescents experienced family conflict, they also showed higher AUC the next day if they had slept less the night prior to conflict, but higher CAR the next day if they had slept more the night prior to conflict. Family conflict and sleep were not directly or interactively related to cortisol slope.

Maternal stress and social support prospectively predict infant inflammation.

Maternal stress has been suggested to be a risk factor for offspring health, while social support has been shown to be a protective factor for offspring functioning. Currently, research has yet to investigate how both of these factors may relate to infant inflammatory processes and associated biological aging in the first years of life. In 48 mother-infant dyads, we investigated whether maternal parenting stress and social support when infants were 12 and 18 months of age were cross-sectionally associated with infant salivary C-reactive protein (sCRP) during these times. In addition, we investigated whether parenting stress and social support were prospectively associated with later sCRP and changes in sCRP from 12 to 18 months of age, as well as whether those changes in sCRP were associated with subsequent infant salivary telomere length (sTL), a marker of biological aging. Analyses revealed that while there were no cross-sectional associations between maternal factors and infant sCRP, maternal parenting stress and social support when infants were 12 months of age predicted infant sCRP at 18 months of age. Further, maternal social support predicted changes in infant sCRP from 12 to 18 months of age. We observed a null association between infant sCRP and sTL. Implications for the ways that maternal mental health and social support may impact biological mechanisms related to disease processes in infants are discussed.

The quality of early infant-caregiver relational attachment and longitudinal changes in infant inflammation across 6 months.

The quality of early caregiver-infant relationships has powerful implications for health trajectories across the lifespan, including associations with adult inflammation. However, because relatively few studies have examined this association during infancy, it remains unclear when this impact occurs and whether it is associated with longitudinal changes in salivary concentrations of inflammation across infancy. In 45 infants, we investigated whether the quality of infant-caregiver attachment (secure vs. insecure) was associated not only with levels of salivary C-reactive protein (sCRP) cross-sectionally, but also with changes in sCRP across 6 months. Interestingly, while there were no cross-sectional associations between infant-caregiver attachment and inflammation at 12 months of age, infant-caregiver attachment security predicted lower levels of sCRP 6 months later. In addition, attachment security predicted decreasing levels of sCRP from 12 months to 18 months of age. Implications for understanding the influence of the quality of early relationships on biological mechanisms related to disease are discussed.

Replication and reproducibility issues in the relationship between C-reactive protein and depression: A systematic review and focused meta-analysis.

One of the most common inflammatory markers examined in depression is C-reactive protein (CRP). However, the magnitude of the association between CRP and depression when controlling for potentially confounding factors such as age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, is unclear. Inconsistencies in other methodological practices, such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. We aggregate studies that examined the association between CRP and depression in two ways. First, a systematic review summarizes how studies of CRP and depression have reported on methodological issues. Second, a tiered meta-analysis aggregates studies that have adhered to various levels of methodological rigor. Findings from the systematic review indicate a lack of protocol detail provided. The effect between depression and CRP was small, but highly significant across all stages of the meta-analysis (p < 0.01). The effect size in the most methodologically rigorous stage of the meta-analysis, which included studies controlling for age, sex, obesity, medical conditions and substance, medication, or psychosocial factors, was small (r = 0.05). There were also only 26 articles in this stage (13% of studies from the systematic review), suggesting that more studies that consistently account for these confounding factors are needed. Additionally, an a priori quality score of methodological rigor was a significant moderator in this stage of the meta-analysis. The effect size was strikingly attenuated (r = 0.005) and non-significant in studies with higher quality scores. We describe a set of recommended guidelines for future research to consider, including sample collection and assaying procedures, data cleaning and statistical methods, and control variables to assess.

Longitudinal outcomes of a therapist-supported digital mental health intervention for depression and anxiety symptoms: A retrospective cohort study.

PURPOSE: This study examined treatment outcomes (depression and anxiety symptoms) up to 24 months after completion of a therapist-supported digital mental health intervention (DMHI). METHODS: The sample consisted of 380 participants who participated in an eight-week DMHI from February 6, 2017 to May 20, 2019. Participants reported depression and anxiety symptoms at eight timepoints from baseline to 24 months. Mixed-effects modelling was used to investigate symptom changes over time. The proportion of participants meeting criteria for treatment response, clinically significant change, and remission of depression and anxiety symptoms were calculated, including proportions demonstrating each outcome sustained up to each timepoint. RESULTS: Multivariate analyses yielded statistically significant reductions in depression (ß = -5.40) and anxiety (ß = -3.31) symptoms from baseline to end of treatment (8 weeks). Symptom levels remained significantly reduced from baseline through 24 months. The proportion of participants meeting criteria for clinical treatment outcomes remained constant over 24 months, although there were linear decreases in the proportions experiencing sustained clinical outcomes. CONCLUSIONS: Treatment gains were made for depression and anxiety symptoms at the end of treatment and up to 24 months. Future studies should determine the feasibility of integrating post-treatment programmes into DMHIs to address symptom deterioration.

Therapist-supported digital mental health intervention for depressive symptoms: A randomized clinical trial.

Depression is a chronic and debilitating mental disorder. Despite the existence of several evidence-based treatments, many individuals suffering from depression face myriad structural barriers to accessing timely care which may be alleviated by digital mental health interventions (DMHI). Accordingly, this randomized clinical trial (ClinicalTrials.gov: NCT04738084) investigated the efficacy of a newer version of the therapist-supported and guided DMHI, the Meru Health Program (MHP), which was recently enhanced with heart rate variability biofeedback and lengthened from 8- to 12-weeks duration, among people with elevated depression symptoms (N = 100, mean age 37). Recruited participants were randomized to the MHP (n = 54) or a waitlist control (n = 46) condition for 12 weeks. The MHP group had greater decreases in depression symptoms compared to the waitlist control (d = -0.8). A larger proportion of participants in the MHP group reported a minimal clinically important difference (MCID) in depression symptoms than participants in the waitlist control group (39.1 % vs. 9.8 %, χ2(1) = 9.90, p = .002). Similar effects were demonstrated for anxiety symptoms, quality of life, insomnia, and resilience. The results confirm the utility of the enhanced MHP in reducing depression symptoms and associated health burdens.

Preliminary Effectiveness of a Therapist-Supported Digital Mental Health Intervention in Reducing Suicidal Ideation.

Suicidal ideation (SI) is a significant public health concern with increasing prevalence. Therapist-supported digital mental health interventions (DMHI) are an emergent modality to address common mental health problems like depression and anxiety, although less is known about SI. This study examined SI trajectories among 778 patients who participated in a therapist-supported DMHI using multilevel models during and up to 6-months post-treatment. Estimates of associated suicide attempts and deaths by suicide were calculated using published data linking PHQ-9-assessed SI to records of suicide attempts and deaths by suicide. The proportion of participants reporting no SI significantly increased between baseline and end-of-treatment (78.02% to 91.00%). Effect sizes of SI changes between baseline and end-of-treatment, 3-month, and 6-month follow-ups were 0.33 (95%CI = 0.27-0.38), 0.32 (95%CI = 0.27-0.38), and 0.32 (95%CI = 0.27-0.38), respectively. Results also indicated an estimated 30.49% reduction (95%CI = 25.15%-35.13%) in suicide attempts and death by suicide across treatment. This study provides preliminary evidence of the effectiveness of a therapist-supported DMHI in reducing SI.

Interpersonal Life Stress and Inflammatory Reactivity as Prospective Predictors of Suicide Attempts in Adolescent Females.

Adolescents' suicidal behavior frequently is preceded by interpersonal stress, but not all who experience distress attempt to end their lives. Recent theories have posited individual differences in stress-related inflammatory reactivity may be associated with psychopathology risk; this study examined inflammatory reactivity as a moderator of the prospective association between interpersonal stress and adolescents' suicidal behavior. Participants included 157 at-risk adolescent females (ages 12 to 16 years) and assessed individual differences in proinflammatory cytokine responses to a brief laboratory-based social stressor, both interpersonal and non-interpersonal life events, and suicidal behavior over an 18-month follow-up period. Measuring levels of the key proinflammatory cytokines interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) before and after an experimentally-induced social stressor, results revealed that blunted cytokine reactivity heightened the effect of high interpersonal stress exposure on risk for suicidal behaviors over the subsequent 9 months. Significant effects were not revealed for non-interpersonally themed stress. Finding highlight the urgent need for more research examining inflammation reactivity among adolescents.